Baseten Provider
Baseten is a platform for running and testing LLMs. It allows you to deploy models that are OpenAI API compatible that you can use with the AI SDK.
Setup
The Baseten provider is available via the @ai-sdk/openai
module as it is compatible with the OpenAI API.
You can install it with
pnpm add @ai-sdk/openai
Provider Instance
To use Baseten, you can create a custom provider instance with the createOpenAI
function from @ai-sdk/openai
:
import { createOpenAI } from '@ai-sdk/openai';
const BASETEN_MODEL_ID = '<deployment-id>';const BASETEN_DEPLOYMENT_ID = null;
// see https://docs.baseten.co/api-reference/openai for more informationconst basetenExtraPayload = { model_id: BASETEN_MODEL_ID, deployment_id: BASETEN_DEPLOYMENT_ID,};
const baseten = createOpenAI({ name: 'baseten', apiKey: process.env.BASETEN_API_KEY ?? '', baseURL: 'https://bridge.baseten.co/v1/direct', fetch: async (url, request) => { const bodyWithBasetenPayload = JSON.stringify({ ...JSON.parse(request.body), baseten: basetenExtraPayload, }); return await fetch(url, { ...request, body: bodyWithBasetenPayload }); },});
Be sure to have your BASETEN_API_KEY
set in your environment and the model deployment id
ready. The deployment_id
will be given after you have deployed the model on Baseten.
Language Models
You can create Baseten models using a provider instance.
The first argument is the served model name, e.g. ultravox
.
const model = baseten('ultravox');
Example
You can use Baseten language models to generate text with the generateText
function:
import { createOpenAI } from '@ai-sdk/openai';import { generateText } from 'ai';
const BASETEN_MODEL_ID = '<deployment-id>';const BASETEN_DEPLOYMENT_ID = null;
// see https://docs.baseten.co/api-reference/openai for more informationconst basetenExtraPayload = { model_id: BASETEN_MODEL_ID, deployment_id: BASETEN_DEPLOYMENT_ID,};
const baseten = createOpenAI({ name: 'baseten', apiKey: process.env.BASETEN_API_KEY ?? '', baseURL: 'https://bridge.baseten.co/v1/direct', fetch: async (url, request) => { const bodyWithBasetenPayload = JSON.stringify({ ...JSON.parse(request.body), baseten: basetenExtraPayload, }); return await fetch(url, { ...request, body: bodyWithBasetenPayload }); },});
const { text } = await generateText({ model: baseten('ultravox'), prompt: 'Tell me about yourself in one sentence',});
console.log(text);
Baseten language models are also able to generate text in a streaming fashion with the streamText
function:
import { createOpenAI } from '@ai-sdk/openai';import { streamText } from 'ai';
const BASETEN_MODEL_ID = '<deployment-id>';const BASETEN_DEPLOYMENT_ID = null;
// see https://docs.baseten.co/api-reference/openai for more informationconst basetenExtraPayload = { model_id: BASETEN_MODEL_ID, deployment_id: BASETEN_DEPLOYMENT_ID,};
const baseten = createOpenAI({ name: 'baseten', apiKey: process.env.BASETEN_API_KEY ?? '', baseURL: 'https://bridge.baseten.co/v1/direct', fetch: async (url, request) => { const bodyWithBasetenPayload = JSON.stringify({ ...JSON.parse(request.body), baseten: basetenExtraPayload, }); return await fetch(url, { ...request, body: bodyWithBasetenPayload }); },});
const result = streamText({ model: baseten('ultravox'), prompt: 'Tell me about yourself in one sentence',});
for await (const message of result.textStream) { console.log(message);}
Baseten language models can also be used in the generateObject
, and streamObject
functions.